| <!--Copyright 2024 The HuggingFace Team. All rights reserved. | |
| Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with | |
| the License. You may obtain a copy of the License at | |
| http://www.apache.org/licenses/LICENSE-2.0 | |
| Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on | |
| an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the | |
| specific language governing permissions and limitations under the License. | |
| --> | |
| # EDMEulerScheduler | |
| The Karras formulation of the Euler scheduler (Algorithm 2) from the [Elucidating the Design Space of Diffusion-Based Generative Models](https://huggingface.co/papers/2206.00364) paper by Karras et al. This is a fast scheduler which can often generate good outputs in 20-30 steps. The scheduler is based on the original [k-diffusion](https://github.com/crowsonkb/k-diffusion/blob/481677d114f6ea445aa009cf5bd7a9cdee909e47/k_diffusion/sampling.py#L51) implementation by [Katherine Crowson](https://github.com/crowsonkb/). | |
| ## EDMEulerScheduler | |
| [[autodoc]] EDMEulerScheduler | |
| ## EDMEulerSchedulerOutput | |
| [[autodoc]] schedulers.scheduling_edm_euler.EDMEulerSchedulerOutput | |